NDLI: EEG signal classification for real-time brain-computer interface applications: A review

Content Provider	IEEE Xplore Digital Library
Author	Khorshidtalab, A. Salami, M. J. E.
Copyright Year	2011
Description	Author affiliation: Department of Mechatronics Engineering, International Islamic University Malaysisa, Gombak, Malaysia (Khorshidtalab, A.; Salami, M. J. E.) Brain-computer interface (BCI) is linking the brain activity to computer, which allows a person to control devices directly with his brain waves and without any use of his muscles. Recent advances in real-time signal processing have made BCI a feasible alternative for controlling robot and for communication as well. Controlling devices using BCI is a crucial aid for people suffering from severe disabilities and more than that, BCIs can replace human to control robots working in dangerous or uncongenial situations. Effective BCIs demand for accurate and real-time EEG signals processing. This paper is to review the current state of research and to compare the performance of different algorithms for real-time classification of BCI-based electroencephalogram signals.
Starting Page	1
Ending Page	7
File Size	107969
Page Count	7
File Format	PDF
ISBN	9781612844350
e-ISBN	9781612844374
DOI	10.1109/ICOM.2011.5937125
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems Support vector machines Brain Computer Interface Hidden Markov models Realtime signal processing EEG Feature extraction Electroencephalography Classification algorithms Brain computer interfaces
Content Type	Text
Resource Type	Article

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